Artificial Theory of Mind and Self-Guided Social Organisation
Michael S. Harr\'e, Jaime Ruiz-Serra, Catherine Drysdale

TL;DR
This paper explores how collective intelligence and human-like social cognition, including Theory of Mind, can inform the development of socially embodied AI systems capable of self-guided social organization.
Contribution
It introduces a framework linking ecological, neuro-physiological, and psychological factors to advance collective AI with human-like social understanding.
Findings
Highlights the importance of Theory of Mind in social AI
Draws analogies between ecological networks and social networks
Discusses potential for self-guided social AI development
Abstract
One of the challenges artificial intelligence (AI) faces is how a collection of agents coordinate their behaviour to achieve goals that are not reachable by any single agent. In a recent article by Ozmen et al this was framed as one of six grand challenges: That AI needs to respect human cognitive processes at the human-AI interaction frontier. We suggest that this extends to the AI-AI frontier and that it should also reflect human psychology, as it is the only successful framework we have from which to build out. In this extended abstract we first make the case for collective intelligence in a general setting, drawing on recent work from single neuron complexity in neural networks and ant network adaptability in ant colonies. From there we introduce how species relate to one another in an ecological network via niche selection, niche choice, and niche conformity with the aim of forming…
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Taxonomy
TopicsOpinion Dynamics and Social Influence
